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Privacy Preservation Using Game-Theoretic Approach

Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

In this chapter, we propose a distributed approach for LBS privacy protection. In order to protect users from a recently highlighted threat model and achieve k-anonymity, we let distributed mobile LBS users generate dummies according to their own privacy needs when the total number of users in a service area is less than k. From a game theoretic perspective, we identify the strategy space of the autonomous and self-interested users in a typical LBS system, and formulate two Bayesian games for the cases with and without the effect of decision timing. The existence and properties of the Bayesian Nash Equilibria for both models are analyzed. Based on the analysis, we further propose a distributed algorithm to optimize user payoffs. Through simulations using real-world privacy data trace, we justify our theoretical results.

Keywords

Mobile User Side Information Privacy Protection Location Base Service Real Identity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.University of FloridaGainesvilleUSA

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